Investigating the persistence of accuracy of genomic predictions over time in broilers

Accuracy of genomic predictions is an important component of the selection response. The objectives of this research were: 1) to investigate trends for prediction accuracies over time in a broiler population of accumulated phenotypes, genotypes, and pedigrees and 2) to test if data from distant generations are useful to maintain prediction accuracies in selection candidates. The data contained 820K phenotypes for a growth trait (GT), 200K for two feed efficiency traits (FE1 and FE2), and 42K for a carcass yield trait (CY). The pedigree included 1,252,619 birds hatched over 7 years, of which 154,318 from the last 4 years were genotyped. Training populations were constructed adding 1 year of data sequentially, persistency of accuracy over time was evaluated using predictions from birds hatched in the three generations following or in the years after the training populations. In the first generation, before genotypes became available for the training populations (first 3 years of data), accuracies remained almost stable with successive additions of phenotypes and pedigree to the accumulated dataset. The inclusion of 1 year of genotypes in addition to 4 years of phenotypes and pedigree in the training population led to increases in accuracy of 54% for GT, 76% for FE1, 110% for CY, and 38% for FE2; on average, 74% of the increase was due to genomics. Prediction accuracies declined faster without than with genomic information in the training populations. When genotypes were unavailable, the average decline in prediction accuracy across traits was 41% from the first to the second generation of validation, and 51% from the second to the third generation of validation. When genotypes were available, the average decline across traits was 14% from the first to the second generation of validation, and 3% from the second to the third generation of validation. Prediction accuracies in the last three generations were the same when the training population included 5 or 2 years of data, and a decrease of ~7% was observed when the training population included only 1 year of data. Training sets including genomic information provided an increase in accuracy and persistence of genomic predictions compared with training sets without genomic data. The two most recent years of pedigree, phenotypic, and genomic data were sufficient to maintain prediction accuracies in selection candidates. Similar conclusions were obtained using validation populations per year.     

Epidemiological studies of pig diseases: 1. Use of French protocols for risk factor assessment to predict the health status of Australian herds

Objective To determine in Australian pig herds the accuracy of French protocols for risk factor assessment.
Procedure Data on health indicators and risk factors were collected for three syndromes, 'pre-weaning diarrhoea', 'post-weaning diarrhoea' and 'respiratory problems', using the French protocols. The protocols were used on 118 occasions in 32 Western Australian pig herds during 3 years (1988 to 1991).
Results There was a wide variation in pre-weaning performance, for example growth rate was 107 to 273 g/day (< 200 g/day in 33% of herds). Respiratory lesions at weaning were associated with poor pre-weaning performance. Post-weaning (21 days after weaning) growth rate was 114 to 408 g/day (< 250 g/day in 54% of herds). In the grower herds, 91% of herds had pneumonia, and growth rate was 439 to 625 g/day (< 550 g/day in 54% of herds). Pleurisy as well as pneumonia was associated with reduced growth rate. The risk factor most closely associated with respiratory health status was air volume per pig.
Conclusion Risk factors were most accurate at predicting the health status in post-weaning problems. A weaning weight of at least 7.9 kg and weaning age of 30 days optimised weaner performance. Stocking densities and shed designs providing at least 3 m³ air volume and 0.6 m² floor space per pig throughout the growing phase should be considered for an improved respiratory health status. Australian pig sheds often do not provide a satisfactory environment for optimum health. The technique of risk factor assessment as an aid to the maintenance of health in pig herds is applicable in Australia, but further research is necessary to determine the most important Australian risk factors.     

Accuracy of genomic prediction using different models and response variables in the Nordic Red cattle population

Breeding animals can be accurately evaluated using appropriate genomic prediction models, based on marker data and phenotype information. In this study, direct genomic values (DGV) were estimated for 16 traits of Nordic Total Merit (NTM) Index in Nordic Red cattle population using three models and two different response variables. The three models were as follows: a linear mixed model (GBLUP), a Bayesian variable selection model similar to BayesA (BayesA*) and a Bayesian least absolute shrinkage and selection operator model (Bayesian Lasso). The response variables were deregressed proofs (DRP) and conventional estimated breeding values (EBV). The reliability of genomic predictions was measured on bulls in the validation data set as the squared correlation between DGV and DRP divided by the reliability of DRP. Using DRP as response variable, the reliabilities of DGV among the 16 traits ranged from 0.151 to 0.569 (average 0.317) for GBLUP, from 0.152 to 0.576 (average 0.318) for BayesA* and from 0.150 to 0.570 (average 0.320) for Bayesian Lasso. Using EBV as response variable, the reliabilities ranged from 0.159 to 0.580 (average 0.322) for GBLUP, from 0.157 to 0.578 (average 0.319) for BayesA* and from 0.159 to 0.582 (average 0.325) for Bayesian Lasso. In summary, Bayesian Lasso performed slightly better than the other two models, and EBV performed slightly better than DRP as response variable, with regard to prediction reliability of DGV. However, these differences were not statistically significant. Moreover, using EBV as response variable would result in problems with the scale of the resulting DGV and potential problem due to double counting.     

Considerations on ethics and animal welfare in extensive pig production: Breeding and fattening Iberian pigs

The extensive pig production in Spain is traditionally characterised by: the use of the Iberian pig, an autochthonous breed perfectly integrated into the environment in which they have developed; a long duration of the productive cycle for about 23–24 months; a high level of animal welfare level, specially in the fattening process with freedom of movement and feeding base on natural sources: acorns and grass, and an equilibrated “dehesa” agro-forestry system where this activity has been developed. Nowadays, the introduction of more intensificated methods due to the increasing demand led to important changes, such as: the shortening of the productive cycle (10–12 months); freeing from the territorial base; changes during the fattening period, fattening with mixed feed and less animal freedom. All these facts may implicate a loss of the animal welfare condition. These circumstances lead us to question it from an ethical point of view.     

Improving production efficiency in the presence of genotype by environment interactions in pig genomic selection breeding programmes

We simulated a genomic selection pig breeding schemes containing nucleus and production herds to improve feed efficiency of production pigs that were cross‐breed. Elite nucleus herds had access to high‐quality feed, and production herds were fed low‐quality feed. Feed efficiency in the nucleus herds had a heritability of 0.3 and 0.25 in the production herds. It was assumed the genetic relationships between feed efficiency in the nucleus and production were low (r_g = 0.2), medium (r_g = 0.5) and high (r_g = 0.8). In our alternative breeding schemes, different proportion of production animals were recorded for feed efficiency and genotyped with high‐density panel of genetic markers. Genomic breeding value of the selection candidates for feed efficiency was estimated based on three different approaches. In one approach, genomic breeding value was estimated including nucleus animals in the reference population. In the second approach, the reference population was containing a mixture of nucleus and production animals. In the third approach, the reference population was only consisting of production herds. Using a mixture reference population, we generated 40–115% more genetic gain in the production environment as compared to only using nucleus reference population that were fed high‐quality feed sources when the production animals were offspring of the nucleus animals. When the production animals were grand offspring of the nucleus animals, 43–104% more genetic gain was generated. Similarly, a higher genetic gain generated in the production environment when mixed reference population was used as compared to only using production animals. This was up to 19 and 14% when the production animals were offspring and grand offspring of nucleus animals, respectively. Therefore, in genomic selection pig breeding programmes, feed efficiency traits could be improved by properly designing the reference population.     

Persistency of accuracy of genomic breeding values for different simulated pig breeding programs in developing countries

Genetic improvement of pigs in tropical developing countries has focused on imported exotic populations which have been subjected to intensive selection with attendant high population‐wide linkage disequilibrium (LD). Presently, indigenous pig population with limited selection and low LD are being considered for improvement. Given that the infrastructure for genetic improvement using the conventional BLUP selection methods are lacking, a genome‐wide selection (GS) program was proposed for developing countries. A simulation study was conducted to evaluate the option of using 60 K SNP panel and observed amount of LD in the exotic and indigenous pig populations. Several scenarios were evaluated including different size and structure of training and validation populations, different selection methods and long‐term accuracy of GS in different population/breeding structures and traits. The training set included previously selected exotic population, unselected indigenous population and their crossbreds. Traits studied included number born alive (NBA), average daily gain (ADG) and back fat thickness (BFT). The ridge regression method was used to train the prediction model. The results showed that accuracies of genomic breeding values (GBVs) in the range of 0.30 (NBA) to 0.86 (BFT) in the validation population are expected if high density marker panels are utilized. The GS method improved accuracy of breeding values better than pedigree‐based approach for traits with low heritability and in young animals with no performance data. Crossbred training population performed better than purebreds when validation was in populations with similar or a different structure as in the training set. Genome‐wide selection holds promise for genetic improvement of pigs in the tropics.     

Efficient approximation of reliabilities for single-step genomic best linear unbiased predictor models with the Algorithm for Proven and Young

The objectives of this study were to develop an efficient algorithm for calculating prediction error variances (PEVs) for genomic best linear unbiased prediction (GBLUP) models using the Algorithm for Proven and Young (APY), extend it to single-step GBLUP (ssGBLUP), and apply this algorithm for approximating the theoretical reliabilities for single- and multiple-trait models in ssGBLUP. The PEV with APY was calculated by block sparse inversion, efficiently exploiting the sparse structure of the inverse of the genomic relationship matrix with APY. Single-step GBLUP reliabilities were approximated by combining reliabilities with and without genomic information in terms of effective record contributions. Multi-trait reliabilities relied on single-trait results adjusted using the genetic and residual covariance matrices among traits. Tests involved two datasets provided by the American Angus Association. A small dataset (Data1) was used for comparing the approximated reliabilities with the reliabilities obtained by the inversion of the left-hand side of the mixed model equations. A large dataset (Data2) was used for evaluating the computational performance of the algorithm. Analyses with both datasets used single-trait and three-trait models. The number of animals in the pedigree ranged from 167,951 in Data1 to 10,213,401 in Data2, with 50,000 and 20,000 genotyped animals for single-trait and multiple-trait analysis, respectively, in Data1 and 335,325 in Data2. Correlations between estimated and exact reliabilities obtained by inversion ranged from 0.97 to 0.99, whereas the intercept and slope of the regression of the exact on the approximated reliabilities ranged from 0.00 to 0.04 and from 0.93 to 1.05, respectively. For the three-trait model with the largest dataset (Data2), the elapsed time for the reliability estimation was 11 min. The computational complexity of the proposed algorithm increased linearly with the number of genotyped animals and with the number of traits in the model. This algorithm can efficiently approximate the theoretical reliability of genomic estimated breeding values in ssGBLUP with APY for large numbers of genotyped animals at a low cost.     

Evaluation of smallholder pig production systems in North Vietnam: Pig production management and pig performances

This study investigated the productive adaptability of pig breeds under different smallholder production conditions in Vietnam, comparing an indigenous with a Vietnamese improved breed. Fieldwork was conducted in four villages with different remoteness in North Vietnam from 2001 to 2002, in 64 households keeping the improved Mong Cai or indigenous Ban as sow breeds and progeny for fattening. Four visits per farm yielded 234 structured interviews. Reproductive performances were derived from 135 litters. Individual weights of pigs (n = 755) were obtained. Data were analysed by regression, linear and generalised linear, especially loglinear models.

Two distinct pig production systems were identified, that differed in remoteness, market access, resource availability, distribution of pig breeds and pig production intensity. Higher performances of 1.4 and 1.5 litters year^− 1, 8.4 and 8.4 piglets weaned litter^− 1, 66.6 and 93.0 kg piglets weaned sow^− 1 year^− 1, and 136 and 177 g day^− 1 ADG were found in two villages near town with semi-intensive production conditions and a high rate of improved Mong Cai sows and MC and LW × MC offspring in the observed population. Lower performances of 1.1 and 1.1 litters year^− 1, 4.6 and 5.5 piglets weaned litter^− 1, 20.5 and 30.9 kg piglets weaned sow^− 1 year^− 1, and 66 and 85 g day^− 1 ADG were observed in parallel to higher incidences of indigenous Ban pigs away from town under extensive conditions. Total live weight offtake per household per year was higher near town and in one village distant to town. MC and LW × MC remained even under demand-driven conditions below the performance potential reported for improved genotypes. Under resource-driven conditions with a saving-oriented production pattern, the higher-yielding but more demanding Mong Cai might not be an efficient production alternative as a further performance reduction can be assumed. A considerable live weight output was observed under resource-driven conditions and with a higher percentage of crossbred LW × Ban offspring in the population, possibly representing a promising production alternative. Factors influencing the performance expression of pigs, and the suitability of different methods for the assessment of performance parameters on-farm are discussed.     

蜂胶的作用及其在猪生产中的应用

本文主要介绍了蜂胶的作用及其在猪生产中的应用。     

A comparison of accuracy validation methods for genomic and pedigree‐based predictions of swine litter size traits using Large White and simulated data

The objective of this study was to compare and determine the optimal validation method when comparing accuracy from single‐step GBLUP (ssGBLUP) to traditional pedigree‐based BLUP. Field data included six litter size traits. Simulated data included ten replicates designed to mimic the field data in order to determine the method that was closest to the true accuracy. Data were split into training and validation sets. The methods used were as follows: (i) theoretical accuracy derived from the prediction error variance (PEV) of the direct inverse (iLHS), (ii) approximated accuracies from the accf90(GS) program in the BLUPF90 family of programs (Approx), (iii) correlation between predictions and the single‐step GEBVs from the full data set (GEBV_Full), (iv) correlation between predictions and the corrected phenotypes of females from the full data set (Y_c), (v) correlation from method iv divided by the square root of the heritability (Y_ch) and (vi) correlation between sire predictions and the average of their daughters' corrected phenotypes (Y_cs). Accuracies from iLHS increased from 0.27 to 0.37 (37%) in the Large White. Approximation accuracies were very consistent and close in absolute value (0.41 to 0.43). Both iLHS and Approx were much less variable than the corrected phenotype methods (ranging from 0.04 to 0.27). On average, simulated data showed an increase in accuracy from 0.34 to 0.44 (29%) using ssGBLUP. Both iLHS and Y_ch approximated the increase well, 0.30 to 0.46 and 0.36 to 0.45, respectively. GEBV_Full performed poorly in both data sets and is not recommended. Results suggest that for within‐breed selection, theoretical accuracy using PEV was consistent and accurate. When direct inversion is infeasible to get the PEV, correlating predictions to the corrected phenotypes divided by the square root of heritability is adequate given a large enough validation data set.     

Investigating maternal effects on production traits in Duroc pigs using animal and sire models

Variance components for production traits were estimated using different models to evaluate maternal effects. Data analysed were records from the South African pig performance testing scheme on 22 224 pigs from 18 herds, tested between 1990 and 2008. The traits analysed were backfat thickness (BFAT), test period weight gain (TPG), lifetime weight gain (LTG), test period feed conversion ratio (FCR) and age at slaughter (AGES). Data analyses were performed by REML procedures in ASREML, where random effects were successively fitted into animal and sire models to produce different models. The first animal model had one random effect, the direct genetic effects, while the additional random effects were maternal genetic and maternal permanent environmental effects. In the sire model, the random effects fitted were sire and maternal grand sire effects. The best model considered the covariance between direct and maternal genetic effects or between sire and maternal grand sire effects. Fitting maternal genetic effects into the animal model reduced total additive variance, while the total additive variance increased when maternal grand sire effects were fitted into the sire model. The correlations between direct and maternal genetic effects were all negative, indicating antagonism between these effects, hence the need to consider both effects in selection programmes. Direct genetic correlations were higher than other correlations, except for maternal genetic correlations of FCR with TPG, LTG and AGES. There has been direct genetic improvement and almost constant maternal ability in production traits as shown by trends for estimated (EBVs) and maternal breeding values (MBVs), while phenotypic trends were similar to those for EBVs. These results suggest that maternal genetic effects should be included in selection programmes for these production traits. Therefore, the animal–maternal model may be the most appropriate model to use when estimating genetic parameters for production traits in this population.     

Accuracy of genomic prediction using imputed whole‐genome sequence data in white layers

There is an increasing interest in using whole‐genome sequence data in genomic selection breeding programmes. Prediction of breeding values is expected to be more accurate when whole‐genome sequence is used, because the causal mutations are assumed to be in the data. We performed genomic prediction for the number of eggs in white layers using imputed whole‐genome resequence data including ~4.6 million SNPs. The prediction accuracies based on sequence data were compared with the accuracies from the 60 K SNP panel. Predictions were based on genomic best linear unbiased prediction (GBLUP) as well as a Bayesian variable selection model (BayesC). Moreover, the prediction accuracy from using different types of variants (synonymous, non‐synonymous and non‐coding SNPs) was evaluated. Genomic prediction using the 60 K SNP panel resulted in a prediction accuracy of 0.74 when GBLUP was applied. With sequence data, there was a small increase (~1%) in prediction accuracy over the 60 K genotypes. With both 60 K SNP panel and sequence data, GBLUP slightly outperformed BayesC in predicting the breeding values. Selection of SNPs more likely to affect the phenotype (i.e. non‐synonymous SNPs) did not improve the accuracy of genomic prediction. The fact that sequence data were based on imputation from a small number of sequenced animals may have limited the potential to improve the prediction accuracy. A small reference population (n = 1004) and possible exclusion of many causal SNPs during quality control can be other possible reasons for limited benefit of sequence data. We expect, however, that the limited improvement is because the 60 K SNP panel was already sufficiently dense to accurately determine the relationships between animals in our data.     

A design for studies on cognitive bias in the domestic pig

Studies on consequences of affect on cognitive processing (cognitive bias) seem to provide proxy measures of the valence (positive/negative) of affective states. This article presents a pilot study testing a design for studies of judgment bias we adapted to the specific needs and abilities of domestic pigs. We used a spatial judgment paradigm, in which subjects learned to discriminate a food rewarded from an unrewarded position of a goal box during a training period, and then were tested for their responses to 3 equidistant intermediate probe positions during a testing period. After the training period, half of the subjects were repeatedly isolated from their social group to manipulate their affective state. Subjects learned the required discrimination task (positive vs. negative stimulus) and showed consistent differences in approach latencies toward and exploration of stimuli of different valence. Hence, the subjects' expectations could be inferred from their behavior. However, repeated social isolation had no effect on judgment of ambiguous stimuli and on both basal and test-related cortisol levels. In conclusion, the spatial judgment approach seems to provide a useful tool to detect and discriminate diverse affective states in domestic pigs based on their responses to graded ambiguous stimuli.     

脂联素的生理作用及其在养猪中的应用前景

脂联素是脂肪组织特异性分泌的一种脂肪细胞因子,具有调控生物体的能量稳态、葡萄糖代谢和脂肪代谢等功能。它通过降低脂肪沉积的效应、减重效应及对胰岛素的增敏效应调控能量分配;此外,还具有抗炎、抗血管损伤功能,可能为治疗相关的动物疾病提供新的靶点。本文介绍了脂联素的来源、分子结构、生物学功能及影响其分泌的因素,阐述了脂联素对动物脂肪沉积的影响及其在脂肪-骨骼肌信号通路中的作用,展望了脂联素在养猪生产中的应用前景。     

Risks associated with preweaning mortality in 855 litters on 39 commercial outdoor pig farms in England

A prospective longitudinal study was carried out on 39 outdoor breeding pig farms in England in 2003 and 2004 to investigate the risks associated with mortality in liveborn preweaning piglets. Researchers visited each farm and completed a questionnaire with the farmer and made observations of the paddocks, huts and pigs. The farmer recorded the number of piglets born alive and stillborn, fostered on and off and the number of piglets that died before weaning for 20 litters born after the visit. Data were analysed from a cohort of 9424 liveborn piglets from 855 litters. Overall 1274 liveborn piglets (13.5%) died before weaning. A mixed effect binomial model was used to investigate the associations between preweaning mortality and farm and litter level factors, controlling for litter size and number of piglets stillborn and fostered. Increased risk of mortality was associated with fostering piglets over 24 h of age, organic certification or membership of an assurance scheme with higher welfare standards, farmer's perception that there was a problem with pest birds, use of medication to treat coccidiosis and presence of lame sows on the farm. Reduced mortality was associated with insulated farrowing huts and door flaps, women working on the farm and the farmer reporting a problem with foxes.     

Optimization of in vitro embryo production and zygote vitrification for the indigenous Vietnamese Ban pig: The effects of different in vitro oocyte maturation systems

The Vietnamese Ban pig is a precious genetic resource that needs to be preserved. In vitro embryo production from in vitro matured (IVM) oocytes is an important tool for the utilization of cryopreserved porcine sperm. The aim of this study was to compare two media for the IVM of Ban pig oocytes. Immature oocytes were subjected to IVM either in a non‐defined (TCM‐199 + pig follicular fluid) or in a defined base medium (POM + epidermal growth factor). At the end of IVM, the oocytes were in vitro fertilized (IVF) with frozen Ban sperm. Ten hours after IVF, the oocytes were either subjected to orcein staining to check fertilization and maturation status or cultured in vitro for 7 days. There was no difference between the two IVM media in terms of percentages of oocyte maturation and blastocyst production. However, the percentage of male pronuclear formation after IVF and the total cell numbers in blastocysts were higher with the defined system. Zygotes obtained by the two IVM systems survived vitrification at similar rates. In conclusion, the two IVM systems were both effective for the production of Ban pig embryos; however, better embryo quality was achieved with the defined one.     

Additional considerations to the use of single‐step genomic predictions in a dominance setting

Recent publications indicate that single‐step models are suitable to estimate breeding values, dominance deviations and total genetic values with acceptable quality. Additive single‐step methods implicitly extend known number of allele information from genotyped to non‐genotyped animals. This theory is well derived in an additive setting. It was recently shown, at least empirically, that this basic strategy can be extended to dominance with reasonable prediction quality. Our study addressed two additional issues. It illustrated the theoretical basis for extension and validated genomic predictions to dominance based on single‐step genomic best linear unbiased prediction theory. This development was then extended to include inbreeding into dominance relationships, which is a currently not yet solved issue. Different parametrizations of dominance relationship matrices were proposed. Five dominance single‐step inverse matrices were tested and described as C¹ , C² , C³ , C⁴ and C⁵ . Genotypes were simulated for a real pig population (n = 11,943 animals). In order to avoid any confounding issues with additive effects, pseudo‐records including only dominance deviations and residuals were simulated. SNP effects of heterozygous genotypes were summed up to generate true dominance deviations. We added random noise to those values and used them as phenotypes. Accuracy was defined as correlation between true and predicted dominance deviations. We conducted five replicates and estimated accuracies in three sets: between all ( S₁ ), non‐genotyped ( S₂ ) and inbred non‐genotyped ( S₃ ) animals. Potential bias was assessed by regressing true dominance deviations on predicted values. Matrices accounting for inbreeding ( C³ , C⁴ and C⁵ ) best fit. Accuracies were on average 0.77, 0.40 and 0.46 in S₁ , S₂ and S₃ , respectively. In addition, C³ , C⁴ and C⁵ scenarios have shown better accuracies than C¹ and C² , and dominance deviations were less biased. Better matrix compatibility (accuracy and bias) was observed by re‐scaling diagonal elements to 1 minus the inbreeding coefficient ( C⁵ ).     

Evaluation of biological and economic efficiency of smallholder pig production systems in North Vietnam

This study evaluates smallholder pig production systems in North Vietnam, comparing a semi-intensive system near a town with good market access, where a Vietnamese improved breed has replaced the indigenous pig breed, and an extensive system away from town, where the indigenous breed still prevails. Fieldwork was conducted in 64 households in four villages. Repeated farm visits yielded 234 structured interviews. Data were analysed by linear models and non-parametric tests. Production inputs and outputs were quantified, and feed use efficiency and economic efficiency were assessed. The gross margin was higher for semi-intensive production with the improved breed, while the benefit–cost ratio was higher under extensive conditions with the indigenous breed. The net benefit did not differ between systems. Twenty-four per cent of farmers yielded a negative net benefit. In one village under extensive conditions, live weight output from indigenous sows with crossbred offspring compared positively with the output from semi-intensive production with improved genotypes, but was associated with high inputs, making production inefficient. Results indicate that improved genotypes might not be an efficient production alternative for saving-oriented production with limited resource supply. Suitability of evaluation parameters, farmers’ production aims, and factors impacting the production success in different systems are discussed.     

Comparison of production systems for efficient use of indigenous pig breeds in developing countries

Conserving pig genetic resources and improving their productivity is important to increase returns over investment in developing countries. The purebred, first‐cross, rotational cross and backcross matings representing production systems based on pig breeds indigenous to the country and exotic pig breeds were investigated. The number of pigs in the nucleus and commercial herds necessary to produce a defined quantity of pork was considered. The amount of heterosis between the indigenous and exotic breeds, superiority in meat production, and degree of inferiority in reproductive performance of the exotic breed compared with that of the indigenous breed were investigated. The number of breeding pigs in the whole system was in the following order: pure breeding (PB) > first‐cross (F1) > rotational cross (RC) > backcross (BC) systems. The number of breeding pigs in the nucleus herds of the RC and BC systems was smaller than that in the nucleus herds of the PB and F1 systems. The degree of inferiority in reproductive performance of the exotic breed compared with that of the indigenous breed affected the efficiency of the production system.